import mxnet as mx
from utils import symbol_utils


def Act(data, act_type, name):
    body = mx.sym.Activation(data=data, act_type='relu', name=name)
    return body


def Conv(data, num_filter=1, kernel=(1, 1), stride=(1, 1), pad=(0, 0), num_group=1, name=None, suffix=''):
    conv = mx.sym.Convolution(data=data, num_filter=num_filter, kernel=kernel, num_group=num_group, stride=stride,
                              pad=pad, no_bias=True, name='%s%s_conv2d' % (name, suffix))
    bn = mx.sym.BatchNorm(data=conv, name='%s%s_batchnorm' % (name, suffix), fix_gamma=True)
    act = Act(data=bn, act_type='relu', name='%s%s_relu' % (name, suffix))
    return act


def ConvOnly(data, num_filter=1, kernel=(1, 1), stride=(1, 1), pad=(0, 0), num_group=1, name=None, suffix=''):
    conv = mx.sym.Convolution(data=data, num_filter=num_filter, kernel=kernel, num_group=num_group, stride=stride,
                              pad=pad, no_bias=True, name='%s%s_conv2d' % (name, suffix))
    return conv


def get_symbol(num_classes, **kwargs):
    data = mx.symbol.Variable(name="data")  # 224
    data = data - 127.5
    data = data * 0.0078125
    version_input = kwargs.get('version_input', 1)
    assert version_input >= 0
    version_output = kwargs.get('version_output', 'E')
    multiplier = kwargs.get('multiplier', 1.0)
    fc_type = version_output
    base_filter = int(32 * multiplier)
    bf = base_filter
    print(version_input, version_output, base_filter)

    if version_input == 0:
        conv_1 = Conv(data, num_filter=bf, kernel=(3, 3), pad=(1, 1), stride=(2, 2), name="conv_1")  # 224/112
    else:
        conv_1 = Conv(data, num_filter=bf, kernel=(3, 3), pad=(1, 1), stride=(1, 1), name="conv_1")  # 224/112
    conv_2_dw = Conv(conv_1, num_group=bf, num_filter=bf, kernel=(3, 3), pad=(1, 1), stride=(1, 1),
                     name="conv_2_dw")  # 112/112
    conv_2 = Conv(conv_2_dw, num_filter=bf * 2, kernel=(1, 1), pad=(0, 0), stride=(1, 1), name="conv_2")  # 112/112
    conv_3_dw = Conv(conv_2, num_group=bf * 2, num_filter=bf * 2, kernel=(3, 3), pad=(1, 1), stride=(2, 2),
                     name="conv_3_dw")  # 112/56
    conv_3 = Conv(conv_3_dw, num_filter=bf * 4, kernel=(1, 1), pad=(0, 0), stride=(1, 1), name="conv_3")  # 56/56
    conv_4_dw = Conv(conv_3, num_group=bf * 4, num_filter=bf * 4, kernel=(3, 3), pad=(1, 1), stride=(1, 1),
                     name="conv_4_dw")  # 56/56
    conv_4 = Conv(conv_4_dw, num_filter=bf * 4, kernel=(1, 1), pad=(0, 0), stride=(1, 1), name="conv_4")  # 56/56
    conv_5_dw = Conv(conv_4, num_group=bf * 4, num_filter=bf * 4, kernel=(3, 3), pad=(1, 1), stride=(2, 2),
                     name="conv_5_dw")  # 56/28
    conv_5 = Conv(conv_5_dw, num_filter=bf * 8, kernel=(1, 1), pad=(0, 0), stride=(1, 1), name="conv_5")  # 28/28
    conv_6_dw = Conv(conv_5, num_group=bf * 8, num_filter=bf * 8, kernel=(3, 3), pad=(1, 1), stride=(1, 1),
                     name="conv_6_dw")  # 28/28
    conv_6 = Conv(conv_6_dw, num_filter=bf * 8, kernel=(1, 1), pad=(0, 0), stride=(1, 1), name="conv_6")  # 28/28
    conv_7_dw = Conv(conv_6, num_group=bf * 8, num_filter=bf * 8, kernel=(3, 3), pad=(1, 1), stride=(2, 2),
                     name="conv_7_dw")  # 28/14
    conv_7 = Conv(conv_7_dw, num_filter=bf * 16, kernel=(1, 1), pad=(0, 0), stride=(1, 1), name="conv_7")  # 14/14

    conv_8_dw = Conv(conv_7, num_group=bf * 16, num_filter=bf * 16, kernel=(3, 3), pad=(1, 1), stride=(1, 1),
                     name="conv_8_dw")  # 14/14
    conv_8 = Conv(conv_8_dw, num_filter=bf * 16, kernel=(1, 1), pad=(0, 0), stride=(1, 1), name="conv_8")  # 14/14
    conv_9_dw = Conv(conv_8, num_group=bf * 16, num_filter=bf * 16, kernel=(3, 3), pad=(1, 1), stride=(1, 1),
                     name="conv_9_dw")  # 14/14
    conv_9 = Conv(conv_9_dw, num_filter=bf * 16, kernel=(1, 1), pad=(0, 0), stride=(1, 1), name="conv_9")  # 14/14
    conv_10_dw = Conv(conv_9, num_group=bf * 16, num_filter=bf * 16, kernel=(3, 3), pad=(1, 1), stride=(1, 1),
                      name="conv_10_dw")  # 14/14
    conv_10 = Conv(conv_10_dw, num_filter=bf * 16, kernel=(1, 1), pad=(0, 0), stride=(1, 1), name="conv_10")  # 14/14
    conv_11_dw = Conv(conv_10, num_group=bf * 16, num_filter=bf * 16, kernel=(3, 3), pad=(1, 1), stride=(1, 1),
                      name="conv_11_dw")  # 14/14
    conv_11 = Conv(conv_11_dw, num_filter=bf * 16, kernel=(1, 1), pad=(0, 0), stride=(1, 1), name="conv_11")  # 14/14
    conv_12_dw = Conv(conv_11, num_group=bf * 16, num_filter=bf * 16, kernel=(3, 3), pad=(1, 1), stride=(1, 1),
                      name="conv_12_dw")  # 14/14
    conv_12 = Conv(conv_12_dw, num_filter=bf * 16, kernel=(1, 1), pad=(0, 0), stride=(1, 1), name="conv_12")  # 14/14

    conv_13_dw = Conv(conv_12, num_group=bf * 16, num_filter=bf * 16, kernel=(3, 3), pad=(1, 1), stride=(2, 2),
                      name="conv_13_dw")  # 14/7
    conv_13 = Conv(conv_13_dw, num_filter=bf * 32, kernel=(1, 1), pad=(0, 0), stride=(1, 1), name="conv_13")  # 7/7
    conv_14_dw = Conv(conv_13, num_group=bf * 32, num_filter=bf * 32, kernel=(3, 3), pad=(1, 1), stride=(1, 1),
                      name="conv_14_dw")  # 7/7
    conv_14 = Conv(conv_14_dw, num_filter=bf * 32, kernel=(1, 1), pad=(0, 0), stride=(1, 1), name="conv_14")  # 7/7
    body = conv_14
    fc1 = symbol_utils.get_fc1(body, num_classes, fc_type)
    return fc1
